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Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis.

ABSTRACT: BACKGROUND:Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further. METHODS:In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. RESULTS:Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4. CONCLUSION:We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

SUBMITTER: Yin Z

PROVIDER: S-EPMC7640415 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis.

Yin Zhenhua Z Wu Dejun D Shi Jianping J Wei Xiyi X Jin Nuyun N Lu Xiaolan X Ren Xiaohan X

BMC cancer 20201104 1

<h4>Background</h4>Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further.<h4>Methods</h4>In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database.<h4>Results</h4>Our analysis identif ...[more]

PMID: 33148208

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Project description:PurposeEsophageal adenocarcinoma (EAC) is the most common type of esophageal cancer in Western countries. It is usually detected at an advanced stage and has a poor prognosis. The aim of this study was to identify key genes and miRNAs in EAC.MethodsThe mRNA microarray data sets GSE1420, GSE26886, and GSE92396 and miRNA data set GSE16456 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were obtained using R software. Functional enrichment analysis was performed using the DAVID database. A protein-protein interaction (PPI) network and functional modules were established using the STRING database and visualized by Cytoscape. The targets of the DEMs were predicted using the miRecords database, and overlapping genes between DEGs and targets were identified. The prognosis-related overlapping genes were identified using Kaplan-Meier analysis and Cox proportional hazard analysis based on The Cancer Genome Atlas (TCGA) database. The differential expression of these prognosis-related genes was validated using the expression matrix in the TCGA database.ResultsSeven hundred and fifteen DEGs were obtained, consisting of 313 upregulated and 402 downregulated genes. The PPI network consisted of 281 nodes; 683 edges were constructed and 3 functional modules were established. Forty-four overlapping genes and 56 miRNA- mRNA pairs were identified. Five genes, FAM46A, RAB15, SLC20A1, IL1A, and ACSL1, were associated with overall survival or relapse-free survival. FAM46A and IL1A were found to be independent prognostic indicators for overall survival, and FAM46A, RAB15, and SLC20A1 were considered independent prognostic indicators for relapse-free survival. Among them, the overexpression of RAB15 and SLC20A1 and lower expression of ACSL1 were also identified in EAC tissues based on the expression matrix in the TCGA database.ConclusionThese prognosis-related genes and differentially expressed miRNA have provided potential biomarkers for EAC diagnosis and treatment.

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Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis.

Publications

Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis.

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